specific method · filed under inference & serving
Dual-kernel batch-invariant attention decoding
A two-kernel strategy developed for batch-invariant attention decoding.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
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Evidence
1 span quoted from the sources, strongest treatment first.
To address this, we develop a dual-kernel strategy for batch-invariant decoding.
usedunclearin DeepSeek-V4DeepSeek
Filed alongside
Other methods under inference & serving :: inference kernel.
Batch-invariant deterministic kernelsCUDA GraphCUDA Graph capture size reductionFlashAttention 3Kernel fusionMoE-side chunkingSynchronization-free static-shape MoE executionTensorRT-LLM multi-head attention backendAvoiding split-KDeepGEMM-based batch-invariant matrix multiplicationDistributed shared memory for cross-SM attention data exchangeDynamic load balancingExp-free TopK kernelExpert-optimized Triton kernelsFA4 sheared-bias attention kernelFlashAttentionFlashAttention 4FlashKDAFP8 GEMMFused AttnRes merge and RMSNorm kernelFused latent down-projection and MoE-router GEMMFused mHC kernelsFused QSA kernelFused RoPE-attention-RoPE-cast kernel